{"id":"W1993304237","doi":"10.3934/mbe.2009.6.301","title":"Culling structured hosts to eradicate vector-borne diseases","year":2009,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Culling; Vector (molecular biology); Disease control; Differential equation; Applied mathematics; Control theory (sociology); Biology; Mathematics; Toxicology; Computer science; Ecology; Control (management); Artificial intelligence; Biotechnology; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003671302,0.0002122627,0.0005318447,0.0001144232,0.00009980465,0.00002575439,0.0002023645,0.0001269845,0.0004606706],"category_scores_gemma":[0.001690907,0.000142652,0.0001239583,0.0003407734,0.0001629152,0.00008773384,0.00004385603,0.0002058344,0.0001929258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003123312,"about_ca_system_score_gemma":0.0000227844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.029864e-7,"about_ca_topic_score_gemma":8.502933e-8,"domain_scores_codex":[0.9984471,0.00002106116,0.0003913636,0.0003650007,0.0002299394,0.0005455032],"domain_scores_gemma":[0.998723,0.0003610927,0.00003647235,0.0002616329,0.00003220017,0.0005855648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002659552,0.000142887,0.00006691399,0.00008252767,0.00001556167,0.0000231815,0.0001298924,0.0005320427,0.007359543,0.9908813,0.00007044937,0.0006691165],"study_design_scores_gemma":[0.0008926177,0.001422794,0.04690816,0.0007943027,0.0002777035,0.0002552806,0.00007381643,0.4263783,0.009335259,0.5121249,0.0006696496,0.0008672577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4799702,0.0001739052,0.4961822,0.0191196,0.000220667,0.0005608473,0.000008270034,0.0003934044,0.003370976],"genre_scores_gemma":[0.978577,0.000006091446,0.01974177,0.001448075,0.000104514,0.00001584152,0.000002657672,0.000009615309,0.00009443765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4986068,"threshold_uncertainty_score":0.5817181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384375282190303,"score_gpt":0.2701349418275029,"score_spread":0.2562911890055998,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}